


'''simple docstring'''


from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tokenizers_available,
    is_torch_available,
    is_vision_available,
)


UpperCAmelCase_						:  Union[str, Any]				  =						{
    'configuration_layoutlmv2': ['LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LayoutLMv2Config'],
    'processing_layoutlmv2': ['LayoutLMv2Processor'],
    'tokenization_layoutlmv2': ['LayoutLMv2Tokenizer'],
}

try:
				if not is_tokenizers_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				UpperCAmelCase_						:  int				  =						['LayoutLMv2TokenizerFast']

try:
				if not is_vision_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				UpperCAmelCase_						:  int				  =						['LayoutLMv2FeatureExtractor']
				UpperCAmelCase_						:  Dict				  =						['LayoutLMv2ImageProcessor']

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				UpperCAmelCase_						:  List[Any]				  =						[
				    'LAYOUTLMV2_PRETRAINED_MODEL_ARCHIVE_LIST',
				    'LayoutLMv2ForQuestionAnswering',
				    'LayoutLMv2ForSequenceClassification',
				    'LayoutLMv2ForTokenClassification',
				    'LayoutLMv2Layer',
				    'LayoutLMv2Model',
				    'LayoutLMv2PreTrainedModel',
				]

if TYPE_CHECKING:
				from .configuration_layoutlmva import LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP, LayoutLMvaConfig
				from .processing_layoutlmva import LayoutLMvaProcessor
				from .tokenization_layoutlmva import LayoutLMvaTokenizer

				try:
								if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .tokenization_layoutlmva_fast import LayoutLMvaTokenizerFast

				try:
								if not is_vision_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .feature_extraction_layoutlmva import LayoutLMvaFeatureExtractor, LayoutLMvaImageProcessor

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_layoutlmva import (
								    LAYOUTLMV2_PRETRAINED_MODEL_ARCHIVE_LIST,
								    LayoutLMvaForQuestionAnswering,
								    LayoutLMvaForSequenceClassification,
								    LayoutLMvaForTokenClassification,
								    LayoutLMvaLayer,
								    LayoutLMvaModel,
								    LayoutLMvaPreTrainedModel,
								)
else:
				import sys

				UpperCAmelCase_						:  str				  =						_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)








'''simple docstring'''


import tempfile
import unittest

from make_student import create_student_by_copying_alternating_layers

from transformers import AutoConfig
from transformers.file_utils import cached_property
from transformers.testing_utils import require_torch


UpperCAmelCase_						:  List[Any]				  =						'sshleifer/bart-tiny-random'
UpperCAmelCase_						:  Tuple				  =						'patrickvonplaten/t5-tiny-random'





@require_torch
class        lowercase__    (		unittest.TestCase   ):





							'''simple docstring'''


							@cached_property
							def UpperCAmelCase_      (       self    ):
											return AutoConfig.from_pretrained(__snake_case    )






							def UpperCAmelCase_      (       self    ):
											_SCREAMING_SNAKE_CASE						,			*_SCREAMING_SNAKE_CASE					:			int							= create_student_by_copying_alternating_layers(__snake_case       ,   tempfile.mkdtemp()       ,   e=1       ,   d=1    )
											self.assertEqual(student.config.num_hidden_layers       ,   1    )






							def UpperCAmelCase_      (       self    ):
											_SCREAMING_SNAKE_CASE						,			*_SCREAMING_SNAKE_CASE					:			int							= create_student_by_copying_alternating_layers(__snake_case       ,   tempfile.mkdtemp()       ,   e=1       ,   d=__snake_case    )






							def UpperCAmelCase_      (       self    ):
											_SCREAMING_SNAKE_CASE						,			*_SCREAMING_SNAKE_CASE					:			str							= create_student_by_copying_alternating_layers(__snake_case       ,   tempfile.mkdtemp()       ,   e=1       ,   d=__snake_case    )
											self.assertEqual(student.config.encoder_layers       ,   1    )
											self.assertEqual(student.config.decoder_layers       ,   self.teacher_config.encoder_layers    )






							def UpperCAmelCase_      (       self    ):
											_SCREAMING_SNAKE_CASE						,			*_SCREAMING_SNAKE_CASE					:			Union[str, Any]							= create_student_by_copying_alternating_layers(__snake_case       ,   tempfile.mkdtemp()       ,   e=1       ,   d=1    )
											self.assertEqual(student.config.encoder_layers       ,   1    )
											self.assertEqual(student.config.decoder_layers       ,   1    )






							def UpperCAmelCase_      (       self    ):
											with self.assertRaises(__snake_case    ):
															create_student_by_copying_alternating_layers(__snake_case       ,   tempfile.mkdtemp()       ,   e=__snake_case       ,   d=__snake_case    )




